Medeiros, Marcelo () (Dept. of Economic Statistics, Stockholm School of Economics) Veiga, Alvaro () (Dept. of Electrical Engineering, Catholic University of Rio de Janeiro)
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This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the Smooth Transition AutoRegressive (STAR) and the AutoRegressive Artificial Artificial Neural Network (AR-ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and constant variance of the error term against the hypothesis that the variance smoothly changes between regimes. The small sample behaviour of the proposed tests is evaluated throw a Monte-Carlo study and the results show that the tests have size close to the nominal one and a good power.
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Length: 24 pages Date of creation: 06 Jun 2000 Date of revision:
15 Jan 2001 Publication status: Published in Journal of Time Series Analysis, 2003, pages 461-482. Handle: RePEc:hhs:hastef:0386
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Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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